Abstract
“Energy” has been one element of the development of human civilization, also a power for national industry, construction and economic development. The green energy has become the cornerstone in sustainable development to secure such energy supply but may accommodate opinions from controversial perspectives when this subject is discussed. This study develops an interactive big data system, which aims at aggregating data from Facebook, PTT, news, and provides an interactive interface for energy domain experts. The “interaction” characterizes the seamless integration between users and the system to construct the controversial issue sets of energy, which could be identified and established autonomously in this study. The approach using tags of the link in two controversial issues can help end-users effectively query on demand. The energy relevant issues can be fully aware and provided to the decision makers from the positive and negative viewpoints.
| Original language | English |
|---|---|
| Title of host publication | Advances in Data Mining |
| Subtitle of host publication | Applications and Theoretical Aspects - 16th Industrial Conference, ICDM 2016, Proceedings |
| Editors | Petra Perner |
| Publisher | Springer Verlag |
| Pages | 139-153 |
| Number of pages | 15 |
| ISBN (Print) | 9783319415604 |
| DOIs | |
| Publication status | Published - 2016 Jan 1 |
| Event | 16th Industrial Conference on Advances in Data Mining, ICDM 2016 - New York, United States Duration: 2016 Jul 13 → 2016 Jul 17 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 9728 |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 16th Industrial Conference on Advances in Data Mining, ICDM 2016 |
|---|---|
| Country | United States |
| City | New York |
| Period | 16-07-13 → 16-07-17 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)
Cite this
}
Development of issue sets from social big data : A case study of green energy and low-carbon. / Huang, Chun Che; Fang, Yu Jie; Lin, Shian Hua; Liang, Wen-Yau; Wu, Shu Rong.
Advances in Data Mining: Applications and Theoretical Aspects - 16th Industrial Conference, ICDM 2016, Proceedings. ed. / Petra Perner. Springer Verlag, 2016. p. 139-153 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9728).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Development of issue sets from social big data
T2 - A case study of green energy and low-carbon
AU - Huang, Chun Che
AU - Fang, Yu Jie
AU - Lin, Shian Hua
AU - Liang, Wen-Yau
AU - Wu, Shu Rong
PY - 2016/1/1
Y1 - 2016/1/1
N2 - “Energy” has been one element of the development of human civilization, also a power for national industry, construction and economic development. The green energy has become the cornerstone in sustainable development to secure such energy supply but may accommodate opinions from controversial perspectives when this subject is discussed. This study develops an interactive big data system, which aims at aggregating data from Facebook, PTT, news, and provides an interactive interface for energy domain experts. The “interaction” characterizes the seamless integration between users and the system to construct the controversial issue sets of energy, which could be identified and established autonomously in this study. The approach using tags of the link in two controversial issues can help end-users effectively query on demand. The energy relevant issues can be fully aware and provided to the decision makers from the positive and negative viewpoints.
AB - “Energy” has been one element of the development of human civilization, also a power for national industry, construction and economic development. The green energy has become the cornerstone in sustainable development to secure such energy supply but may accommodate opinions from controversial perspectives when this subject is discussed. This study develops an interactive big data system, which aims at aggregating data from Facebook, PTT, news, and provides an interactive interface for energy domain experts. The “interaction” characterizes the seamless integration between users and the system to construct the controversial issue sets of energy, which could be identified and established autonomously in this study. The approach using tags of the link in two controversial issues can help end-users effectively query on demand. The energy relevant issues can be fully aware and provided to the decision makers from the positive and negative viewpoints.
UR - http://www.scopus.com/inward/record.url?scp=84978952304&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84978952304&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-41561-1_11
DO - 10.1007/978-3-319-41561-1_11
M3 - Conference contribution
AN - SCOPUS:84978952304
SN - 9783319415604
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 139
EP - 153
BT - Advances in Data Mining
A2 - Perner, Petra
PB - Springer Verlag
ER -